Human Fallen detection Using deep Learning

Description

For the last few decades, human posture recognition has gained mammoth popularity specifically in elderly fall detection. This study proposes a modified deep learning neural network architecture using Open Pose library for two category problem of human fall detection. Open Pose library computes and draws 18 points skeleton on frames. The proposed approach achieves an accuracy on publicly available, standard Multi Camera Fall dataset and outperforms existing state-of-the-art deep learning image classification using LSTM which have an accuracy respectively.